The latest from the data assimilation research testbed: Powerful new assimilation algorithms, advances in efficiency and capabilities, new model and observation interfaces, and novel results

Raeder, Kevin; Gharamti, Mohamad; Johnson, Benjamin K.; Kershaw, Helen; Huo, X.; Kugler, L.; Kodikara, T.; Raczka, Brett; Smith, Marlena; Liu, J.; Labriola, J.D.; Ishraque, F.; Hagan, D.; Anderson, Jeffrey

Raeder, K., Gharamti, M., Johnson, B. K., Kershaw, H., Huo, X., … Kugler, L. (2023). The latest from the data assimilation research testbed: Powerful new assimilation algorithms, advances in efficiency and capabilities, new model and observation interfaces, and novel results. In AMS Annual Meeting 2023. American Meteorological Society (AMS): Denver, CO, US.

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Author(s)

Kevin Raeder-NCAR/UCAR

Mohamad Gharamti-NCAR/UCAR

Benjamin K. Johnson-NCAR/UCAR

Helen Kershaw-NCAR/UCAR

X. Huo

L. Kugler

T. Kodikara

Brett Raczka-NCAR/UCAR

Marlena Smith-NCAR/UCAR

J. Liu

J.D. Labriola

F. Ishraque

D. Hagan

Jeffrey Anderson-NCAR/UCAR

Title

The latest from the data assimilation research testbed: Powerful new assimilation algorithms, advances in efficiency and capabilities, new model and observation interfaces, and novel results

Date

2023-01-12

Resource Type

conference material

Conference

AMS Annual Meeting 2023

Meeting Sponsor

American Meteorological Society (AMS)

Peer Review

Non-refereed

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OpenSky Citable URL

http://n2t.net/ark:/85065/d7ht2tfk

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The latest from the data assimilation research testbed: Powerful new assimilation algorithms, advances in efficiency and capabilities, new model and observation interfaces, and novel results

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